In some cases, it may be desirable to create a compressed version of data. For example, a business intelligence application might create a compressed version of a warehouse data index to reduce an amount of memory or disk space required to store the index and/or to improve performance of the application.
The use of a single encoding technique to compress such information, however, may have disadvantages. For example, one encoding technique might be inefficient when the density of the information is relatively low (e.g., the information includes many long strings of “1” or “0”). Similarly, another encoding technique might be inefficient when the density is relatively high (e.g., the information is more random in nature).
It would therefore be desirable to provide improved methods and systems that facilitate the compression of information such as business data in an efficient manner.